A Real-time Approach for Autonomous Detection and Tracking of Moving Objects from UAV

被引：0
|
作者：
Sadeghi-Tehran, Pouria [1 ]
Clarke, Christopher [1 ]
Angelov, Plamen [1 ]
机构：
[1] Univ Lancaster, Sch Comp & Commun, Intelligent Syst Lab, Data Sci Grp, Lancaster LA1 4YW, England
来源：
2014 IEEE SYMPOSIUM ON EVOLVING AND AUTONOMOUS LEARNING SYSTEMS (EALS) | 2014年
关键词：
autonomous object detection; mobile visual surveillance platform; UAV;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken from a real UAV and the evaluation results are demonstrated in this paper.
引用
收藏
页码：43 / 49
页数：7
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